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Resting metabolic rate and its adjustments as predictors of risk protein-energy wasting in hemodialysis patients

Background: The purpose of the present study was to explore the association between resting metabolic rate (RMR) and protein-energy wasting (PEW) risk in Chinese hemodialysis patients by age and gender subgroup. Methods: RMR and body composition (body cell mass (BCM) and fat mass) of 774 patients un...

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Autores principales: Da, Jingjing, Long, Yanjun, Li, Qian, Yang, Xia, Yuan, Jing, Zha, Yan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Portland Press Ltd. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8150161/
https://www.ncbi.nlm.nih.gov/pubmed/33704424
http://dx.doi.org/10.1042/BSR20210010
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author Da, Jingjing
Long, Yanjun
Li, Qian
Yang, Xia
Yuan, Jing
Zha, Yan
author_facet Da, Jingjing
Long, Yanjun
Li, Qian
Yang, Xia
Yuan, Jing
Zha, Yan
author_sort Da, Jingjing
collection PubMed
description Background: The purpose of the present study was to explore the association between resting metabolic rate (RMR) and protein-energy wasting (PEW) risk in Chinese hemodialysis patients by age and gender subgroup. Methods: RMR and body composition (body cell mass (BCM) and fat mass) of 774 patients undergoing hemodialysis were estimated by bio-electrical impedance analysis (BIA). Anthropometric data were collected by a standard measurement protocol, and the upper arm muscle circumference (AMC) was calculated. Biochemical nutritional and dialysis parameters were obtained. Linear regression analysis was used to analyze the relationship among RMR, body composition and nutritional factors. Results: The mean age was 54.96 ± 15.78 years. RMR level in patients was 1463.0 (1240.5, 1669.0) kcal/d. In multiple linear regression models, BCM, left calf circumference (LCC), fat mass were the determinants association with RMR (P<0.001). Among the patients in the sample, 133 (17.2%) had been diagnosed with PEW per International Society of Renal Nutrition and Metabolism (ISRNM) criteria and 363 (46.9%) were being at risk PEW. The area under the receiver-operating characteristic curve (AUC) of RMR for predicting risk PEW was greater than RMR/BCM and RMR/body surface area (BSA). When the cutoff of RMR was 1481 kcal/d it had the higher sensitivity and specificity (82 and 42%), and the AUC was 0.68 in elderly maintenance hemodialysis (MHD) patients (P<0.001). After adjustment for potential confounders, lowest RMR quartile level (<1239) increased the risk of PEW (OR = 4.71, 95% CI: 1.33–16.64, P=0.016) in all patients. Conclusions: Older patients with PEW have a lower RMR reduction. RMR and RMR/BCM may play the role in objective screening to detect risk PEW in MHD patients, especially in males.
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spelling pubmed-81501612021-06-07 Resting metabolic rate and its adjustments as predictors of risk protein-energy wasting in hemodialysis patients Da, Jingjing Long, Yanjun Li, Qian Yang, Xia Yuan, Jing Zha, Yan Biosci Rep Metabolism Background: The purpose of the present study was to explore the association between resting metabolic rate (RMR) and protein-energy wasting (PEW) risk in Chinese hemodialysis patients by age and gender subgroup. Methods: RMR and body composition (body cell mass (BCM) and fat mass) of 774 patients undergoing hemodialysis were estimated by bio-electrical impedance analysis (BIA). Anthropometric data were collected by a standard measurement protocol, and the upper arm muscle circumference (AMC) was calculated. Biochemical nutritional and dialysis parameters were obtained. Linear regression analysis was used to analyze the relationship among RMR, body composition and nutritional factors. Results: The mean age was 54.96 ± 15.78 years. RMR level in patients was 1463.0 (1240.5, 1669.0) kcal/d. In multiple linear regression models, BCM, left calf circumference (LCC), fat mass were the determinants association with RMR (P<0.001). Among the patients in the sample, 133 (17.2%) had been diagnosed with PEW per International Society of Renal Nutrition and Metabolism (ISRNM) criteria and 363 (46.9%) were being at risk PEW. The area under the receiver-operating characteristic curve (AUC) of RMR for predicting risk PEW was greater than RMR/BCM and RMR/body surface area (BSA). When the cutoff of RMR was 1481 kcal/d it had the higher sensitivity and specificity (82 and 42%), and the AUC was 0.68 in elderly maintenance hemodialysis (MHD) patients (P<0.001). After adjustment for potential confounders, lowest RMR quartile level (<1239) increased the risk of PEW (OR = 4.71, 95% CI: 1.33–16.64, P=0.016) in all patients. Conclusions: Older patients with PEW have a lower RMR reduction. RMR and RMR/BCM may play the role in objective screening to detect risk PEW in MHD patients, especially in males. Portland Press Ltd. 2021-04-30 /pmc/articles/PMC8150161/ /pubmed/33704424 http://dx.doi.org/10.1042/BSR20210010 Text en © 2021 The Author(s). https://creativecommons.org/licenses/by/4.0/This is an open access article published by Portland Press Limited on behalf of the Biochemical Society and distributed under the Creative Commons Attribution License 4.0 (CC BY) (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Metabolism
Da, Jingjing
Long, Yanjun
Li, Qian
Yang, Xia
Yuan, Jing
Zha, Yan
Resting metabolic rate and its adjustments as predictors of risk protein-energy wasting in hemodialysis patients
title Resting metabolic rate and its adjustments as predictors of risk protein-energy wasting in hemodialysis patients
title_full Resting metabolic rate and its adjustments as predictors of risk protein-energy wasting in hemodialysis patients
title_fullStr Resting metabolic rate and its adjustments as predictors of risk protein-energy wasting in hemodialysis patients
title_full_unstemmed Resting metabolic rate and its adjustments as predictors of risk protein-energy wasting in hemodialysis patients
title_short Resting metabolic rate and its adjustments as predictors of risk protein-energy wasting in hemodialysis patients
title_sort resting metabolic rate and its adjustments as predictors of risk protein-energy wasting in hemodialysis patients
topic Metabolism
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8150161/
https://www.ncbi.nlm.nih.gov/pubmed/33704424
http://dx.doi.org/10.1042/BSR20210010
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